Plenty of exploration algorithms directly seek novel information about the environment dynamics. Some of them [1]}, [2]}, [3]}, [4]} motivate an agent to explore via an additional intrinsic reward. Most of these algorithms depend on a prediction error of some trainable model to measure how novel a transition is and assign an intrinsic reward depending on the novelty.
